With the popularization of smart phones, many users utilize lock screen software to protect their privacy on their mobile phones, beautify their mobile phones, and reduce incorrect operation. Eyeprint recognition lock screen software is lock screen software for protecting privacy on users' mobile phones. Each person's eye texture may be different, and may be unlikely to change significantly. The eyeprint recognition lock screen software utilizes this principle to determine whether or not a user is an owner of the mobile phone by means of eyeprint analysis.
The procedures of the eyeprint recognition lock screen software may be as below: in using for the first time, the user may input his/her own eyeprint information, which may be similar to face recognition lock screen software. Also, an alternative unlocking method may need to be inputted. This may be because image recognition lock screen software may have a certain probability of failure in unlocking the screen. An alternative unlocking method, such as a password or nine-grid pattern, may be preset so that the alternative unlocking method is enabled once the eyeprint recognition is failed.
The eyeprint recognition lock screen software may be as follows: a plurality of eye images of the user may be acquired by using a front-facing camera, then data processing may be performed on these images to acquire the user's eyeprint information, and the eyeprint information may be stored in the mobile phone locally. When the user unlocks the mobile phone, the eyeprint recognition software may turn on the front-facing camera to reacquire the user's eyeprint information, and then it may be determined whether or not the user is the owner of the mobile phone by comparing the eyeprint recognition with the prestored eyeprint information.
The eyeprint recognition lock screen software may utilize a front-facing camera to acquire eye image information of the user, and then process and analyze the image data. Therefore, requirements for image quality from the front-facing camera may be relatively higher. Moreover, the software may be frequently used, thus the user may have higher requirements for speed. However, a certain starting time may be needed to start the front-facing camera, which may make the user experience not smooth, to the disadvantage of the user.
If the time from starting the front-facing camera to acquiring the first frame of an image can be shortened as much as possible, the eyeprint recognition speed can be accelerated and the user experience can be improved. One solution can be to improve the hardware technology of the front-facing camera and improve the CPU processing speed. However, it can be difficult to implement these means. In addition, cost and power consumption may be increased as well.
Therefore, the prior art needs to be improved and developed.